Limits...
Gating multiple signals through detailed balance of excitation and inhibition in spiking networks.

Vogels TP, Abbott LF - Nat. Neurosci. (2009)

Bottom Line: We illustrate gating through detailed balance in large networks of integrate-and-fire neurons.We show successful gating of multiple signals and study failure modes that produce effects reminiscent of clinically observed pathologies.Provided that the individual signals are detectable, detailed balance has a large capacity for gating multiple signals.

View Article: PubMed Central - PubMed

Affiliation: Center for Neurobiology and Behavior, Department of Physiology and Cellular Biophysics, Columbia University College of Physicians and Surgeons, New York, New York, USA.

ABSTRACT
Recent theoretical work has provided a basic understanding of signal propagation in networks of spiking neurons, but mechanisms for gating and controlling these signals have not been investigated previously. Here we introduce an idea for the gating of multiple signals in cortical networks that combines principles of signal propagation with aspects of balanced networks. Specifically, we studied networks in which incoming excitatory signals are normally cancelled by locally evoked inhibition, leaving the targeted layer unresponsive. Transmission can be gated 'on' by modulating excitatory and inhibitory gains to upset this detailed balance. We illustrate gating through detailed balance in large networks of integrate-and-fire neurons. We show successful gating of multiple signals and study failure modes that produce effects reminiscent of clinically observed pathologies. Provided that the individual signals are detectable, detailed balance has a large capacity for gating multiple signals.

Show MeSH

Related in: MedlinePlus

Detailed Balance in a Networka) Average firing rate of the sender neurons responding to a sinusoidally varying input. b) Voltage trace of a randomly selected excitatory receiver neuron. Red trace: single trial. Black trace: the average subthreshold membrane potential over 100 trials. c) Average membrane currents of the excitatory receiver neurons. Excitatory and inhibitory currents are plotted in red and blue respectively, the net current, including voltage-dependent leak and constant background currents, is plotted in black. d) Blue trace: average firing rate of the inhibitory receiver neurons. Red histogram: average firing rate of the excitatory receiver neurons. e) Average firing rate of the entire network. f) Spike raster for 30 randomly chosen excitatory receiver neurons. Conditions shown are: No signal: All neurons fire at background rates. Balanced signal: Sender neurons fire in a correlated manner in response to oscillatory input and project the input firing pattern to both excitatory and inhibitory receiver neurons. Inhibitory receiver neurons reproduce the input pattern, preventing their excitatory neighbors from doing the same. Unbalanced signal: By decreasing the responsiveness of the inhibitory receiver neurons, the signal balance in the excitatory receiver neurons shifts in favor of excitation, and the signal is revealed in their firing pattern. All firing rates and averages are calculated in 5 ms bins.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC2693069&req=5

Figure 2: Detailed Balance in a Networka) Average firing rate of the sender neurons responding to a sinusoidally varying input. b) Voltage trace of a randomly selected excitatory receiver neuron. Red trace: single trial. Black trace: the average subthreshold membrane potential over 100 trials. c) Average membrane currents of the excitatory receiver neurons. Excitatory and inhibitory currents are plotted in red and blue respectively, the net current, including voltage-dependent leak and constant background currents, is plotted in black. d) Blue trace: average firing rate of the inhibitory receiver neurons. Red histogram: average firing rate of the excitatory receiver neurons. e) Average firing rate of the entire network. f) Spike raster for 30 randomly chosen excitatory receiver neurons. Conditions shown are: No signal: All neurons fire at background rates. Balanced signal: Sender neurons fire in a correlated manner in response to oscillatory input and project the input firing pattern to both excitatory and inhibitory receiver neurons. Inhibitory receiver neurons reproduce the input pattern, preventing their excitatory neighbors from doing the same. Unbalanced signal: By decreasing the responsiveness of the inhibitory receiver neurons, the signal balance in the excitatory receiver neurons shifts in favor of excitation, and the signal is revealed in their firing pattern. All firing rates and averages are calculated in 5 ms bins.

Mentions: We explored the idea of detailed balance in a large network of roughly 20,000 integrate-and-fire neurons with both short- and long-range connectivity (Fig. 1a, methods). With appropriately adjusted parameters, this network operates in a globally balanced manner, producing irregular, asynchronous activity in the absence of any time-varying or random external input 5–8. The distribution of firing rates for the network is approximately exponential with an average firing rate per neuron of 8 Hz (Fig. 1c), the distribution of average membrane potentials is approximately Gaussian with a mean of −60 mV (Fig. 1d), the distribution of interspike intervals (ISIs) is broad with peaks reflecting normal firing and bursting (Fig. 1e), and the distribution of coefficients of variation for the ISIs is centered at a value slightly greater than 1 (Fig. 1f). Average excitatory and inhibitory membrane currents are of approximately equal magnitude and the net current is near zero (Fig. 2c, first column), indicating the globally balanced state of the network. This network model is intended to provide a sparse representation of the neurons over a fairly large area, not a full description of a single local circuit such as a cortical column.


Gating multiple signals through detailed balance of excitation and inhibition in spiking networks.

Vogels TP, Abbott LF - Nat. Neurosci. (2009)

Detailed Balance in a Networka) Average firing rate of the sender neurons responding to a sinusoidally varying input. b) Voltage trace of a randomly selected excitatory receiver neuron. Red trace: single trial. Black trace: the average subthreshold membrane potential over 100 trials. c) Average membrane currents of the excitatory receiver neurons. Excitatory and inhibitory currents are plotted in red and blue respectively, the net current, including voltage-dependent leak and constant background currents, is plotted in black. d) Blue trace: average firing rate of the inhibitory receiver neurons. Red histogram: average firing rate of the excitatory receiver neurons. e) Average firing rate of the entire network. f) Spike raster for 30 randomly chosen excitatory receiver neurons. Conditions shown are: No signal: All neurons fire at background rates. Balanced signal: Sender neurons fire in a correlated manner in response to oscillatory input and project the input firing pattern to both excitatory and inhibitory receiver neurons. Inhibitory receiver neurons reproduce the input pattern, preventing their excitatory neighbors from doing the same. Unbalanced signal: By decreasing the responsiveness of the inhibitory receiver neurons, the signal balance in the excitatory receiver neurons shifts in favor of excitation, and the signal is revealed in their firing pattern. All firing rates and averages are calculated in 5 ms bins.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2693069&req=5

Figure 2: Detailed Balance in a Networka) Average firing rate of the sender neurons responding to a sinusoidally varying input. b) Voltage trace of a randomly selected excitatory receiver neuron. Red trace: single trial. Black trace: the average subthreshold membrane potential over 100 trials. c) Average membrane currents of the excitatory receiver neurons. Excitatory and inhibitory currents are plotted in red and blue respectively, the net current, including voltage-dependent leak and constant background currents, is plotted in black. d) Blue trace: average firing rate of the inhibitory receiver neurons. Red histogram: average firing rate of the excitatory receiver neurons. e) Average firing rate of the entire network. f) Spike raster for 30 randomly chosen excitatory receiver neurons. Conditions shown are: No signal: All neurons fire at background rates. Balanced signal: Sender neurons fire in a correlated manner in response to oscillatory input and project the input firing pattern to both excitatory and inhibitory receiver neurons. Inhibitory receiver neurons reproduce the input pattern, preventing their excitatory neighbors from doing the same. Unbalanced signal: By decreasing the responsiveness of the inhibitory receiver neurons, the signal balance in the excitatory receiver neurons shifts in favor of excitation, and the signal is revealed in their firing pattern. All firing rates and averages are calculated in 5 ms bins.
Mentions: We explored the idea of detailed balance in a large network of roughly 20,000 integrate-and-fire neurons with both short- and long-range connectivity (Fig. 1a, methods). With appropriately adjusted parameters, this network operates in a globally balanced manner, producing irregular, asynchronous activity in the absence of any time-varying or random external input 5–8. The distribution of firing rates for the network is approximately exponential with an average firing rate per neuron of 8 Hz (Fig. 1c), the distribution of average membrane potentials is approximately Gaussian with a mean of −60 mV (Fig. 1d), the distribution of interspike intervals (ISIs) is broad with peaks reflecting normal firing and bursting (Fig. 1e), and the distribution of coefficients of variation for the ISIs is centered at a value slightly greater than 1 (Fig. 1f). Average excitatory and inhibitory membrane currents are of approximately equal magnitude and the net current is near zero (Fig. 2c, first column), indicating the globally balanced state of the network. This network model is intended to provide a sparse representation of the neurons over a fairly large area, not a full description of a single local circuit such as a cortical column.

Bottom Line: We illustrate gating through detailed balance in large networks of integrate-and-fire neurons.We show successful gating of multiple signals and study failure modes that produce effects reminiscent of clinically observed pathologies.Provided that the individual signals are detectable, detailed balance has a large capacity for gating multiple signals.

View Article: PubMed Central - PubMed

Affiliation: Center for Neurobiology and Behavior, Department of Physiology and Cellular Biophysics, Columbia University College of Physicians and Surgeons, New York, New York, USA.

ABSTRACT
Recent theoretical work has provided a basic understanding of signal propagation in networks of spiking neurons, but mechanisms for gating and controlling these signals have not been investigated previously. Here we introduce an idea for the gating of multiple signals in cortical networks that combines principles of signal propagation with aspects of balanced networks. Specifically, we studied networks in which incoming excitatory signals are normally cancelled by locally evoked inhibition, leaving the targeted layer unresponsive. Transmission can be gated 'on' by modulating excitatory and inhibitory gains to upset this detailed balance. We illustrate gating through detailed balance in large networks of integrate-and-fire neurons. We show successful gating of multiple signals and study failure modes that produce effects reminiscent of clinically observed pathologies. Provided that the individual signals are detectable, detailed balance has a large capacity for gating multiple signals.

Show MeSH
Related in: MedlinePlus